{"id":"W2021086301","doi":"10.2135/cropsci2014.03.0203","title":"Mega‐environment Analysis and Test Location Evaluation Based on Unbalanced Multiyear Data","year":2014,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Biplot; Variety (cybernetics); Statistics; Mega-; Computer science; Biology; Data mining; Mathematics; Genotype; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001303168,0.00005402483,0.00006097727,0.00002469873,0.0002437872,0.000105103,0.0003118379,0.00001951525,0.0000934051],"category_scores_gemma":[0.0003708043,0.00002185088,0.000009764261,0.0006322426,0.0001210942,0.00008462531,0.00007293758,0.00002918076,0.00001206711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001713322,"about_ca_system_score_gemma":0.000008835536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000873296,"about_ca_topic_score_gemma":0.00009287953,"domain_scores_codex":[0.9990219,0.00002741009,0.00007769326,0.0003526228,0.0003947002,0.0001256124],"domain_scores_gemma":[0.9995316,0.0001858459,0.0000447016,0.0001287925,0.00004584521,0.00006321492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000004782185,0.00005699845,0.1500057,0.000002554687,0.000004024508,1.422783e-7,0.00002549325,0.009914336,0.6223997,0.00004329474,0.0000522142,0.2174909],"study_design_scores_gemma":[0.00003356595,0.00004827496,0.5093562,0.00000298594,0.00001937569,1.091647e-7,0.000007568247,0.4884467,0.001549781,0.00001640748,0.000479264,0.00003977473],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985051,0.00001758449,0.000515156,0.0004668794,0.00003313477,0.00008976096,0.00002258938,0.000009229472,0.0003405893],"genre_scores_gemma":[0.9991877,0.000008164494,0.0005459899,0.0001156205,0.00003993046,0.000002556868,0.00008467958,2.108892e-7,0.00001512812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6208499,"threshold_uncertainty_score":0.1875038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05568089528776104,"score_gpt":0.2489252226860636,"score_spread":0.1932443273983026,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}